Estimating the impact of COVID-19 self-test availability and modifications in test-strategy on overall test uptake using an experimental vignette study

To inform future Dutch COVID-19 testing policies we did an experimental vignette study to investigate whether inclusion of the less reliable lateral flow tests (self-tests) would change test-uptake sufficiently to improve population-level test sensitivity. A representative sample (n = 3,270) participated in a 2-by-2 online experiment to evaluate the effects of test-guidelines including self-testing advice (IV1), and the effects of self-test availability (IV2) on expected test uptake (PCR test, self-test or no test) and sensitivity of the overall test strategy (primary outcome). Across four scenarios, changing test advice did not affect expected testing behaviour. Self-test availability, however, increased the timeliness of testing, the number of people testing, and overall test strategy sensitivity. Based on these findings, we recommend that (national) policy facilitates a supply of self-tests at home, for example through free and pro-active distribution of test-kits during a pandemic. This could substantially enhance the chances of timely detecting and isolating patients.

would an increase in self-testing (lower sensitivity) increase overall test-uptake sufficiently to compensate for a possible decline in PCR-testing (higher sensitivity)?
Why was this transition in preference for self-testing observed in the first place?The practical benefits of self-tests are probably one of the main reasons self-test use increased, in the absence of government guidance.Self-tests are relatively easy to use independently and can provide immediate results, as a positive test result implies infectiousness.This also directly affects the tester as symptomatic people with a negative test result were not required to stay at home.A faster diagnosis would also contribute to the timeliness of contact tracing.In accordance with this line of thought, the WHO advised that self-testing should be offered in addition to professionally administered testing services 8 .Given these advantages, it is plausible that more people would test when self-testing is recommended in case of symptoms in addition to PCR testing.This could potentially also lead to people testing more promptly after symptom presentation, and more willingness to repeatedly test when regularly experiencing symptoms.
Besides government recommendations on what test to use, having self-tests readily available-as opposed to having to purchase them when symptomatic (which could also be a moment of increased risk of transmission)-could be another important factor influencing test uptake.Quasi-experimental research has shown that testing at MHS test facilities increases if the distance to test facilities decreases 9 .Other experimental evidence shows that willingness to use self-tests decreases when their costs increase 10 but also that availability of tests influences isolation intention 11 .In the Netherlands, self-tests are widely available at supermarkets and pharmacies for approximately 3 euros per unit, whereas in countries such as the United Kingdom people could order self-tests free online.We were interested in examining the potential impact of people having self-tests available at home when experiencing symptoms as opposed to having to purchase them or asking someone else to do so.This could provide valuable insights for advising the government to pro-actively distribute free self-test supplies to Dutch citizens.
Given the impossibility of carrying out this research in a real-life randomized trial due to the time-sensitivity of the policy change and practical reasons, we decided to conduct a vignette study on the role of self-tests in close collaboration with epidemiologists and virologists with expertise in COVID-19 testing to advise the Dutch Outbreak Management Team and government.An experimental vignette allows researchers to manipulate independent variables and creates insight into causal relationships which made it a good design for studying test expectations 12 .
In this study we used an online, 2-by-2 vignette to investigate two hypotheses: first, that advising symptomatic people to either self-test or test at an MHS test facility, as opposed to only test at an MHS test facility, increases the probability of detecting positive cases, through an increase in testing and a decrease of time to testing.Second, that the availability of self-tests at home as opposed to having to purchase them, increases the probability of detecting positive cases, through an increase in testing and a testing more promptly after symptom onset.Additionally we explored if the probability of detecting positive cases would decline over time, as people were expected to test less frequently after consecutive episodes of symptoms, and if government advice and the availability of self-tests at home could counter this decline.
All scenarios were carefully designed by following the best practice recommendations to enhance accuracy and experimental realism 12 .Consenting participants were each presented with four episodes of symptoms over four consecutive months in the near future.The type of symptoms in each scenario, ranging from one to multiple symptoms, were based on their actual distribution in the population.Participants were first prompted to depict their typical activities on the relevant weekday in an open text box, which, in the vignettes, featured the initial symptoms occurring on a Tuesday.This step aimed to enhance realism and increase immersion.Next, they were asked to indicate whether-given their symptoms-they expected to not test, go to an MHS test facility or use a self-test that day.If participants did not select the MHS test facility (the optimal test), they were told their symptoms persisted for another 2 days and were asked again what test choice they expected to make.We assessed participants behavioural expectations, as this should reflect behavioural intentions (I plan to do x) adjusted for other influential factors such as past behaviour or specific circumstances on that day.Some studies suggest that behavioural expectations are better predictors of behaviour than behavioural intentions, although the evidence is mixed [13][14][15][16][17] .
To test the hypotheses, respondents were randomly allocated to scenarios describing the testing advice: (1) 'When you have corona-related symptoms, get tested at an MHS test facility' (current government recommendation) or the adjusted advice: 'When you have corona-related symptoms, get tested at an MHS test facility.If this is not possible, use a self-test'; and testing availability: (2) Having self-tests available at home versus not having a supply at home, when COVID-19 symptoms present.The primary outcome was overall strategy sensitivity: an average COVID-19 test sensitivity score based on participants' test choices on day 1 and by day 3 of symptoms across all four scenarios, taking into account differences in self-test versus PCR tests detection probability (sensitivity) 7,18 and considering that viral load is highest at the time of symptom onset 19,20 .Additionally, we examined whether participants opted for testing sooner, whether more people opted for testing, and whether this changed over time.

Participant flow
Of the 6,053 participants who were approached for participation and were selected by an online research panel on demographic representativeness, 3,589 consented.Of those, 319 were excluded due to: fast completion (< 4 min; n = 17), not finishing the questionnaire (n = 286) and not answering crucial questions (n = 16) as per standard protocol from the data collection agency (not described in pre-registration).See Fig. 1 for participant flow diagram.

Descriptive statistics
From a total of 3,270 participants, 50.8% were female.Their median age was 53.3 (standard deviation = 17.3) years and 40.2% was highly educated.79.5% said to have a Dutch background and 20.2% said to have a migration background (7.7% non-western and 12.5% western).Respondents reported to live alone (29.8%), with a partner (39.2%) or with a partner and children (20.5%).See Supplementary Materials (S1) for more details on demographics.
Across scenarios, respondents assigned to experience multiple symptoms (coughing, sneezing and a slight fever) relative to those assigned to experience one mild symptom indicated that they would test more often (90.3% vs. 74.9%),would do so sooner (77.3% vs. 53.5% immediately), and preferred to do so at an MHS test facility (57%) rather than by means of a self-test (19%) or by means of a self-test followed by a test at an MHS test facility (14%) (see Supplementary Materials S2).
By the third day of symptoms (day 1 and day 3 inclusive), respondents on average opted to test in 78.8% across the four episodes of symptoms (46.9% MHS test facility, 37.5% self-test and 15.5% both; 59.5% tested on day 1).Participants willingness to test varied with time (76.8%November, 81.6% December, 79.4% January, 77.3% February), with the highest test rate before the Christmas holidays: a behaviour we had actually observed in December 2020 21 .

Primary analyses
We calculated the overall strategy sensitivity score (the probability of detecting positive cases) by converting the type of test chosen into the respective sensitivity scores on day 1 and by day 3 of symptoms averaged over all four scenarios, see "Methods" for details.There was no effect of changing the test advice on the overall strategy sensitivity score (F(2, 3265) = 0.43, p = 0.654).There was a significant effect of self-test availability at home on the overall strategy sensitivity scores, showing higher sensitivity scores when self-tests were available at home (F(2, 3265) = 38.5, p < 0.001, ηp2 = 0.023).This effect was present on day 1 (F(1, 3266) = 67.8,p < 0.001, ηp2 = 0.020) and still prevalent by day 3 of symptoms (F(1, 3266) = 19.3,p < 0.001, ηp2 = 0.006).There was no significant interaction between test advice and self-test availability (F(2, 3265) = 1.209, p = 0.299).Strategy sensitivity scores are shown in Fig. 2. www.nature.com/scientificreports/

Secondary analysis
Next we analysed whether participants opted for testing sooner, and whether more people opted for testing.Test availability had a significant effect on the number of people that expected to test either at an MHS test facility or self-test (F(2, 3265) = 59.42, p < 0.001, ηp2 = 0.035).Moreover, when self-test were available at home, people expected to test sooner as more participants indicated to test on Day 1 than participants without self-tests at home (F(1, 3266) = 117.87,p < 0.001, ηp2 = 0.035).The significant effects found for testing sooner and more often are driven by the increase in use of self-tests.Also, more participants expected to test (by day 3 of symptoms) with self-tests at home than participants without self-tests at home (F(1, 3266) = 51.03,p < 0.001, ηp2 = 0.015).There was no effect of changing the test advice on expected test uptake or time to testing (F(2, 3265) = 0.31, p = 0.736).
The shift in choice of testing behaviour is shown in Fig. 3. On day 1, expected self-test use doubled resulting in 21.6% difference between groups using self-tests if self-tests were available at home.This comes paired with a decrease of 7.7% of testing at MHS test facilities.

Consecutive episodes of symptoms over time on strategy sensitivity
We expected that strategy sensitivity would decline over time and that people would expect to test less after consecutive episodes of symptoms.However, we also expected that changing the testing advice towards allowing  www.nature.com/scientificreports/for self-tests in case of symptoms, and having self-tests available at home would counter this decline.Indeed, the consecutive episodes of symptoms over time yielded a significant main effect by day 1 (F(2.99,9775.38)= 155.23,p = < 0.001, ηp2 = 0.045) and by day 3 of symptoms (F(2.97,9690.01)= 34.57,p ≤ 0.001, ηp2 = 0.01).A Greenhouse-Geisser correction was used due to a violation of sphericity.Pairwise comparisons show that the increase in overall strategy sensitivity was especially large from November to December, after which a small decline set in, yet sensitivity scores remain higher than the start in November (Fig. 4a,b).The four consecutive episodes of symptoms over time showed a significant interaction with testing advice on strategy sensitivity scores on day 1 (F(3, 3264) = 3.27, p = 0.020, η2 = 0.003) suggesting that the effect of testing advice varied over time: strategy sensitivity scores were slightly higher for the current government guideline testing advice (test at an MHS test facility) during the first two months, and then slightly higher for the (self-) testing advice during the last 2 months.This effect was, however minimal, no longer apparent by day 3 (F(3, 3264) = 1.158, p = 0.324).No other effects were found on consecutive episodes of symptoms, testing advice and availability of self-tests.

Discussion
In this vignette study we found that having self-tests available at home-but not the change in test advicesubstantially increased respondents expected test uptake, reduced time to testing, and led to an increase in the overall strategy sensitivity.Following this study the Dutch Outbreak Management Team advised the government to provide free self-tests to all Dutch citizens.An advice that was, however, not followed-up because of market regulation issues.Free self-tests were already provided to people attending food banks, and to students.
In the study, we observed no changes in expected test uptake following a change in testing advice.We note that quite a number of people had already been using self-tests to determine if their symptoms were due to COVID-19.This could explain why we did not observe a difference in people's expected testing behaviour.It could also be possible that the message was not correctly comprehended by the respondents, as the message was not pre-tested.However, the scenario was under direct consideration by the Dutch Outbreak Management Team during the time of the study.After this study was conducted, Dutch governmental testing advice changed to include a recommendation to self-test when experiencing symptoms.Survey research has since shown that people did report using more self-tests after the advice changed (39% with corona-related symptoms) than before (28.7%) 1 .Nevertheless this increase could have been caused by the increased attention for COVID-19 due to the simultaneous infection peak that occurred upon the introduction of Omicron.
Having self-tests available at home decreased the expected time to testing and substantially increased the number of people who expected to test.Modelling studies have shown that frequent testing, i.e. increasing COVID-19 detection probability, is beneficial for mitigation of COVID-19 [4][5][6] .Furthermore, viral shedding is highest on or just before onset of symptoms 19 , and early transmission could therefore be reduced with sooner testing.This may indicate that providing free self-tests can help mitigate pandemics.Some governments, such as in the UK, have  www.nature.com/scientificreports/ of symptoms per scenario and averaged over all four scenarios.We refer to this accumulated score as "by day 3 of symptoms".Participants who chose to visit the MHS test facility on day 1 were not asked about their most likely behaviour again on day 3, therefore scores from day 1 were used to calculate sensitivity scores by day 3. Sensitivity scores of self-tests on day 1 are higher than day 3 as viral loads were observed to peak at the onset of symptoms and subsequently decrease 19,20

Power
In our sample size calculations we estimated a two tailed t-test to calculate the difference between two independent groups.This resulted in a total of 1,302 participants for 95% power (α = 0.05).As three days were scheduled for data collection, we oversampled and sent out 6.053 invitations.

Statistical methods
Sensitivity scores (day 1 and by day 3) were normally distributed based on the Skewness (day 1: − 0.27, by day 3: − 1.09) and Kurtosis (day 1: − 1.28, day 3: 0.06).Variance between groups was not equal, as shown by a significant Levene's test for sensitivity scores on day 1 (F(3, 3266) = 6.469, p < 0.001), and by day 3 (F(3, 3266) = 25.10,p < 0.001) and Box's test of equality of covariance matrices was significant (F(9, 119192744) = 13.594,p < 0.001) and therefore not all assumptions were met for parametric testing.Yet based on the large sample size and the central limit theorem, parametric tests were used to analyse the data.
As we hypothesised that changing the governmental advice on testing, and having self-tests available at home would increase the strategy sensitivity for citizens with COVID-19 symptoms on day 1 and by day 3 we used a Multivariate GLM with Bonferroni correction.Secondary outcomes, predicting that respondents would test sooner and more often, were also analysed using Multivariate GLM.
Finally, to analyse the predicted decline in strategy sensitivity over time, due to a repeated incidence of symptoms over time, we used a repeated measures ANOVA for strategy sensitivity scores on day 1 and by day 3. Analyses were done in SPSS version 28.

Figure 3 .
Figure 3. Percentages of selected testing behaviours with COVID-19 symptoms averaged over 4 scenarios by testing advice (a) and availability of self-tests (b) on day 1 of symptoms and by day 3 of symptoms.By day 3 also contains participants who chose to visit the MHS test facility on day 1.Percentages above 100% represent participants who expected to use a self-test on day 1, and expected to go to the MHS test facility on day 3.

Figure 4 .
Figure 4. Strategy sensitivity scores for the four scenarios over time, based on choice of testing behaviour with COVID-19 symptoms by testing advice (a) and availability of self-tests (b) on the first day of symptoms and by day 3 of symptoms.
. Secondary outcomes were willingness to test sooner (day 1, self-tests or MHS test facility, averaged over four scenarios); and if respondents would test more often (by the third day of symptoms, self-tests or MHS test facility, averaged over four scenarios).